code: def generate_batch(self, n: int, batch_size: int):
      partitions = []
      for _ in range(batch_size):
          k = np.random.randint(1, 10)
          partition = np.random.multinomial(n, np.ones(k) / k, size=1)[
              0
          ]
          partitions.append(partition)
      return partitions
  
file_path: neural-structured-learning/research/neural_clustering/data_generators/mog_test.py
imports: from absl.testing import absltest
  from absl.testing import parameterized
  from neural_clustering.data_generators import mog
  import numpy
label_desc: Use image node_id 1 for calling the DummyPartitionGenerator obj's underlying member method code with example usage: obj.generate_batch(n, batch_size) and returns: partitions